Alfonso Iorio MDPhD McMaster University Canada Disclosures McMaster University has received research consultancy and educational funding for Population PK projects from Bayer Grifols ID: 682880
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Slide1
Using pharmacokinetics to individualize hemophilia therapy
Alfonso Iorio,
MD,PhD
McMaster University, CanadaSlide2
Disclosures
McMaster University has received research, consultancy and educational funding for Population PK projects from Bayer,
Grifols
,
NovONordisk
,
Octapharma
, Pfizer
I am the co-PI of the WAPPS-Hemo projectSlide3Slide4
4
Hemophilia treatment
Comprehensive care is the cornerstone of effective hemophilia treatment
Prophylactic factor replacement
therapy
1960s, Sweden
non-severe
hemophilia patients do not
bleed spontaneously
Many guidelines, no
consensus on optimal treatment
regimenSlide5
Regulatory level
Concentrates approved by proving their bio-equivalence
Formal PK studies
Clinical level
Prophylaxis
“empirically” managed by targeting a (0.01 IU/mL) target
level
Peri
-surgical management based on longitudinal factor level
measurements
ITI success/failure judged upon by ”normalization” of half-life
Pharmacokinetics and HemophiliaSlide6
6
Pharmacokinetics of factor concentrates
Time (h)
Factor Activity (% of normal)
1%
In vivo recovery (IVR) =
(
C
post
–
C
pre
)/Dose
Volume of distribution similar to plasma volume (3-4 L)
Does not predict half-life or trough
Targeted
trough
: historically 1-2%
Goal of drug therapy to keep activity above targeted trough
Terminal half-life (time taken to reduce activity by half)
mean 10-14 hours for FVIII (>12
yrs
)
mean 18 hours for FVIII extended half-life
Little difference between plasma-derived and recombinant FVIII
McEneny-King et al.
Expert
Opin
Drug Meta
Toxicol
.
2016.
19:
1-9.Slide7
Determining individual PK – e.g. FVIII
7
Historical
ISTH guidelines
(dense sampling)
Designed to
understand the average PK of a concentrate
10 or 11 blood samples over a period of
32-72
h after infusing 25-50
IU/kg at baseline
12-15 patients
with
a crossover
design
Lee M et al. 2001. The design and analysis of pharmacokinetic studies of coagulation factors. ISTH Website, Scientific and Standardization Committee Communication p. 1–9.
New ISTH guidelines
(
popPK
+ sparse sampling)
Focus
on individual PK
estimation
2-3
samples for one
patient
Use a population pharmacokinetic model
&
individual samples to derive individual PK estimates
Iorio A,
Blanchette
V,
Blatny
J, Collins P, Fischer K, Neufeld
E
J
Thromb
Haemost
. 2017 Oct 12.
doi
: 10.1111/jth.13867.Slide8
Determining individual PK – e.g. FVIII
8
Historical
ISTH guidelines
(dense sampling)
Designed to
understand the average PK of a concentrate
10 or 11 blood samples over a period of
32-72
h after infusing 25-50
IU/kg at baseline
12-15 patients
with
a crossover
design
Lee M et al. 2001. The design and analysis of pharmacokinetic studies of coagulation factors. ISTH Website, Scientific and Standardization Committee Communication p. 1–9.
Time
WashoutSlide9
Determining individual PK – e.g. FVIII
9
New ISTH guidelines
(
popPK
+ sparse sampling)
Focus
on individual PK
estimation
2-3
samples for one
patient
Use a population pharmacokinetic model
&
individual samples to derive individual PK estimates
Iorio A,
Blanchette
V,
Blatny
J, Collins P, Fischer K, Neufeld
E
J
Thromb
Haemost
. 2017 Oct 12.
doi
: 10.1111/jth.13867.
Time
24
48
4
24
48
4
Washout
Fixed doseSlide10
Determining individual PK – e.g. FVIII
10
Historical
ISTH guidelines
(dense sampling)
Lee M et al. 2001. The design and analysis of pharmacokinetic studies of coagulation factors. ISTH Website, Scientific and Standardization Committee Communication p. 1–9.
New ISTH guidelines
(
popPK
+ sparse sampling)
Iorio A,
Blanchette
V,
Blatny
J, Collins P, Fischer K, Neufeld
E
J
Thromb
Haemost
. 2017 Oct 12.
doi
: 10.1111/jth.13867.
Washout
WashoutSlide11
Woodstock 1969Slide12
Drug A: 12+/-3
hrs
Drug B: 16+/-3
hrs
Two basic concept to understand tailoring
Understanding variability
Applying population averages vs individualized PK profilesSlide13
Understanding variability to define a dosing strategy
13
Concentration
Subject
Minimum effective concentration
Maximum
concentration
Patients have similar PK
Individual PK similar over time
Generic population dose
(e.g. 10 mg/kg)
Infusion
1
Infusion
2Slide14
Understanding variability to define a dosing strategy
14
Concentration
Subject
Minimum effective concentration
Maximum
concentration
Infusion
1
Infusion
2
Patients have
different
PK
Individual PK varies over time
Can’t define
a regimenSlide15
Understanding variability to define a dosing strategy
15
Concentration
Subject
Minimum effective concentration
Maximum
concentration
Infusion
1
Infusion
2
Patients have
different
PK
Individual PK similar over time
Individualized doseSlide16
PK variability: why we cannot use population estimatesSlide17
PK variability: why we cannot use population estimatesSlide18
Time (
hrs
)
0 12 24 36 48 60 72 84 96
Log [
plasma activity]
10
1
(Terminal) HL
Individual variability in the response to treatment
Inter subject variability
PK variability: why we cannot use population estimatesSlide19
Back-of-napkin individual PK profiling?Slide20
The WAPPS-Hemo
co-investigator network
20
The WAPPS-Hemo
network:
114
registered
HTC
32
different
countries
1550 patients
2459 infusions
www.wapps-hemo.orgSlide21
Single patient report
Single patient data
Estimating PK for single individuals on the base of 2-4 samples
Web-applicationSlide22
Single patient report
Single patient data
Estimating PK for single individuals on the base of 2-4 samples
Web-applicationSlide23
Single patient report
Single patient data
Estimating PK for single individuals on the base of 2-4 samples
Web-application
Online PPK engine
(NONMEM)Slide24
Single patient report
Single patient data
Online PPK engine
(NONMEM)
Brand specific Source individual PK data
Control files for
bayesian
individual estimation
Product 1
Product 3
Product 4
Product 5
Others..
Product 2
Offline PPK
modeling
Brand specific PPK models
Estimating PK for single individuals on the base of 2-4 samples
Web-applicationSlide25
Single patient report
Single patient data
Online PPK engine
(NONMEM)
Brand specific Source individual PK data
Control files for
bayesian
individual estimation
Product 1
Product 3
Product 4
Product 5
Others..
Product 2
Offline PPK
modeling
Brand specific PPK models
patients
patients
patients
Web-application
Interactive simulatorSlide26
WAPPS i
nputs and outputs
26Slide27Slide28
Thanks –
and questions welcome